论文标题
非参数回归的同时置信带，部分缺失协变量
Simultaneous confidence bands for nonparametric regression with partially missing covariates
论文作者
论文摘要
在本文中，我们根据非参数回归的反选择概率考虑了一个加权的局部线性估计量，随机缺少协变量。得出了估计器和真实回归函数之间最大偏差的渐近分布，并构建了渐近准确的同时置信带。在已知的选择概率时，回归函数的估计量被证明是有效的。通过支持我们的渐近理论的模拟研究检查有限样本性能。通过对加拿大2010/2011青年学生调查的数据集的分析来证明所提出的方法。
In this paper, we consider a weighted local linear estimator based on the inverse selection probability for nonparametric regression with missing covariates at random. The asymptotic distribution of the maximal deviation between the estimator and the true regression function is derived and an asymptotically accurate simultaneous confidence band is constructed. The estimator for the regression function is shown to be oracally efficient in the sense that it is uniformly indistinguishable from that when the selection probabilities are known. Finite sample performance is examined via simulation studies which support our asymptotic theory. The proposed method is demonstrated via an analysis of a data set from the Canada 2010/2011 Youth Student Survey.
